tbuckley/cabot-search huggingface dataset:
Utilizing data and artificial intelligence to optimize treatment room scheduling and staffing.
Authors: Larry Edward Bilbrey, Harshavardhana Paramasiviah, Shridar Iyengar, Bhaskar Anepu, Susan A Frailley, Stephen Matthew Schleicher, Ram Iyengar, Natalie R. Dickson
Journal: Journal of Clinical Oncology (2022)

436 Background: Tennessee Oncology is a large community oncology practice with over 30 clinics providing 89,000 treatments per year across Tennessee and northern Georgia. Tennessee Oncology’s scheduling application was unable to optimally schedule treatment appointments. This scheduling gap was causing frequent patient delays and employee extended hours. Tennessee Oncology partnered with Smirta, Inc., to develop a data and artificial intelligence (AI) driven scheduling overlay platform that would optimize and simplify cancer treatment scheduling as well as predict scheduling patterns and resource needs. Methods: Named OncoSmart, the scheduling optimization platform ingests historic scheduling data, detailed clinic configuration data including provider and nursing schedules, and available resource data such as treatment room chairs. Utilizing AI, the platform generates optimal scheduling recommendations matching the specific set of services that need to be scheduled. The platform overlays the current scheduling app and provides dynamic, real-time recommendations based on current resource (treatment room, provider, etc.) schedule availabilities and bookings. Tennessee Oncology piloted the scheduling optimization platform at 1 clinic and has currently expanded the pilot to 12 additional clinics. Results: After various ranges of clinic pilot times (6 months to 2 years), Tennessee Oncology treatment volumes have increased by 7%. In parallel to this increase, the optimization platform has helped decrease extended hours by over 32%. The original pilot site has shown major improvement in all 4 primary key performance indicators (KPI): treatment volume +12%; Chair utilization +12%; treatment delay -9%; extended hours -82%. Additionally, using the platform’s predictive analytics capabilities, analyses have been completed to generate optimal treatment scheduling patterns as well as optimal treatment nursing staffing models. Conclusions: Within a short period after deployment, Smirta Inc’s OncoSmart has helped Tennessee Oncology identify better treatment scheduling options for these 13sites. The scheduling optimization platform has proven to be very effective in identifying optimal treatment scheduling strategies and in identifying critical resource bottlenecks. The platform’s clinic management, optimization, nurse assignment, business intelligence, and resource management modules has empowered Tennessee Oncology to better manage critical clinical resources and reduce staff overtime during a period of growth.
The financial impact of reducing drug waste with biosimilar transition of trastuzumab in the Oncology Care Model for the U.S. Oncology Network.
Authors: Jennifer Fernandez, Puneeth Indurlal, Jody S. Garey, Neal Dave, Richard Cleveland, Jody Agena, Rajat Malhotra, Lalan S. Wilfong
Journal: Journal of Clinical Oncology (2022)

11 Background: The Oncology Care Model (OCM), a 6-year long Medicare value-based care program, rewards practices for decreasing total cost of care (TCOC) compared to a benchmark price, while maintaining high quality cancer care. Care services for enrolled patients are divided into 6-month episodes within 1-year time intervals called Performance Periods (PP). One approach to reducing TCOC is reducing the expenditure for drug waste. In mid-2017, trastuzumab (HER2-targeted monoclonal antibody) 420 mg multi-dose vial (MDV) was discontinued and replaced with a 150 mg single-dose vial (SDV), leading to wastage of the remaining partial quantities of the SDV after preparation of a patient-defined dose. The increased drug waste led to an increase in the total drug cost of trastuzumab and TCOC. Late 2019, MDV and SDV biosimilar trastuzumab products were introduced, and The US Oncology Network (The Network) practices adopted the MDV biosimilar as a strategy to reduce drug waste and TCOC. This study highlights the impact of trastuzumab drug waste on TCOC. Methods: Claims data for 14 Network practices, participating in OCM, were assessed. The financial impact of drug waste and TCOC for The Network’s transition from MDV trastuzumab to SDV trastuzumab in 2017, and from SDV trastuzumab to the MDV biosimilar trastuzumab in 2020 was evaluated. Results: With the use of MDV trastuzumab during OCM PP1, drug waste accounted for 0.05% of the total dose of trastuzumab. After having to shift from MDV to SDV during PP2, as a result of the packaging change, trastuzumab drug waste increased to 10.25% of the total dose, with an increase in TCOC by 0.25% ($2M) per PP during PPs 3-7. As The Network practices adopted the use of MDV biosimilar trastuzumab starting in PP8, drug waste declined 57% to 4.4% of the total dose in PP9, reducing the drug waste component of TCOC by $1.4M (0.16%). Had all SDV trastuzumab doses been transitioned to the MDV biosimilar, an additional $600K (0.09%) in TCOC could have been reduced in PP9. Conclusions: TCOC fluctuations can be driven by not just increasing costs or increased utilization, but also by drug packaging and increasing drug waste. The discontinuation of MDV trastuzumab resulted in a substantial financial impact on drug waste, TCOC, and cost for patients. Swift transition to biosimilar MDV trastuzumab within The Network helped to significantly reduce drug waste and its impact on TCOC in the OCM. Trastuzumab biosimilars, in addition to being cost-effective alternatives to biological therapeutics, offer significant cost savings via drug waste reduction.
Lessons learned from a lung cancer screening patient navigation program at a safety-net hospital system.
Authors: Andrea R Semlow, Vijaya Subbu Natchimuthu, Simon Craddock Lee, David E Gerber, Hong Zhu, Heidi A. Hamann, Travis Browning, Noel O. Santini, Jessica L. Lee
Journal: Journal of Clinical Oncology (2022)

121 Background: As part of a CPRIT prevention services grant led by UTSW, Parkland Health adapted a patient navigation model previously piloted in 2017 to optimize low-dose computed tomography (LDCT) imaging for lung cancer screening and evidence-based tobacco cessation services. Methods: Non-clinical patient navigators (PN) contacted patients with a LDCT order to discuss their lung scan and smoking cessation options via telephone encounters. The PN has three planned touchpoints to assess patient knowledge, identify barriers, and refer to appropriate resources. Program evaluation data has been collected monthly for enrolled patients (n = 460) from August 2021-June 2022 via REDCap and EPIC. Navigation excluded patients who were incarcerated, had no phone number listed in medical record, or patients opted out of the program on intake. Results: Of the LDCT-eligible patients, PNs were able to complete two or more navigation calls with 55.62% of patients assigned. 77% of patients completed their first LDCT, compared to 80% in the initial trial. The most common barriers to screening completion included transportation (n = 38), insurance coverage (n = 22), and cost (n = 9). Of the navigated patients who were active smokers (75%), 33% scheduled at least one smoking cessation-related visit. Some patients unresponsive to conversations about quitting, were responsive to language around “reducing” tobacco use. Conclusions: Disproportionately under- and uninsured, Parkland Health patients face a variety of barriers to screening. As a result, PN staff must balance reaching all patients with a LDCT order and spending additional time navigating patients with complex barriers. To address these barriers, the PN program facilitates coordination of patients between primary care providers, radiology operations, smoking cessation clinics, patient financial services, lung diagnostic clinic, and social work. For example, patients can schedule a smoking cessation visit directly with our PN instead of being referred. As Parkland has a decentralized LCS program model, having embedded non-clinical PNs within existing roles in the cancer center, like medical practice assistants, increases continuity of care. These individuals have the benefit from day-to-day knowledge of downstream services that bolster their ability to connect patients to external services to address barriers.
Impact of wallet cards compared to conventional chemotherapy education in patients with newly-diagnosed cancer.
Authors: Anika Bhargava, Nikita Jain, Adam Rojan, Phuong Ngo, Brian Dong
Journal: Journal of Clinical Oncology (2022)

363 Background: According to American Cancer Society, 1.9 million new cases of cancer were diagnosed in year 2021, majority of who will undergo chemotherapy (1). With these treatments, there is often an overwhelming amount of information given to patients. We will first assess the percentage of new cancer patients that can recall their cancer treatments with the current patient education format. We then aim to improve patient understanding of their treatment with the introduction of a chemotherapy wallet card. Methods: This is a single center prospective cohort study at the University of Louisville, Brown Cancer Center. In phase one 50 new patients will be recruited from various oncology clinics who will receive conventional verbal chemotherapy education. On cycle two of their treatment, we will administer a survey (figure 1) to assess their understanding of their regimen. In phase two we will recruit 50 new patients and introduce a chemotherapy wallet card filled by the pharmacist to be given during their chemotherapy education and administer the survey on cycle two. We will then compare these two populations to evaluate the impact of the chemotherapy wallet cards. Results: Preliminary results from the first phase have been obtained of 15 newly diagnosed cancer patients. Surveys obtained on cycle two revealed 100% patients correctly identified their cancer diagnosis and 60% were able to correctly name their chemotherapy regimen. 53% of patients were able to identify three correct treatment side effects. Conclusions: Preliminary results show 60% of patients have suboptimal identification of their chemotherapy regimens. Previous studies have shown many patients will visit the emergency department in their first year of treatment. This is of concern as patients may not be able to provide accurate information of their current treatment to these providers resulting in suboptimal care. Our goal will be to see if chemotherapy wallet cards will help to increase patient knowledge and improve patient quality of care.[Table: see text]
Relationships among illness understanding, information preferences, and adherence to oral anticancer therapy.
Authors: Joely A. Centracchio, Jamie M. Jacobs, Jennifer S. Temel, Joseph A. Greer
Journal: Journal of Clinical Oncology (2022)

250 Background: Patients prescribed oral anticancer therapy receive less support for adherence and symptom monitoring from oncologists compared to infusional cancer therapy, which can result in lower quality care and worse disease outcomes. Identifying factors related to adherence can guide efforts to develop patient-centered interventions. The goal of this analysis was to examine associations among patients’ illness understanding, information preferences, and oral anticancer therapy adherence. Methods: We conducted a secondary analysis of a randomized trial testing the efficacy of a mobile application to improve assessment of symptoms and treatment adherence. Eligible patients included adults diagnosed with cancer prescribed oral anticancer therapy. To assess adherence, participants stored their medication for three months in a Medication Event Monitoring System (MEMS) bottle that electronically records the date and time the bottle is opened. At baseline, participants completed the Prognosis and Treatment Perceptions Questionnaire, which assesses patients’ illness understanding and information preferences in communicating with oncologists. We conducted linear regression to examine associations among patients’ illness understanding, information preferences, and medication adherence. Results: The study included 181 patients prescribed oral anticancer therapy (Mean age = 53.30 years; 53.6% female; 87.8% white). The most common cancer types were hematologic (33.1%), lung (18.2%), and breast (14.4%) malignancies. Two-thirds (66.9%) were prescribed oral targeted therapies, and 35.5% self-identified as terminally ill. Controlling for intervention effects, patients who reported wanting as many details as possible related to their cancer and treatment had higher MEMS adherence over the three-month study period (B = 12.84, 95%CI: 3.65, 22.03, p =.006) versus those who preferred to know fewer details. Also, patients who reported that it was extremely important for them to know their prognosis had higher adherence (B = 9.93, 95%CI: 1.73, 18.13, p =.018) versus those who rated knowing about prognosis as less important, though this relationship was moderated by illness understanding. Specifically, in the subgroup of patients reporting that they were not terminally ill, the association between wanting to know about prognosis and MEMS adherence remained significant (p =.006), which was not the case for patients identifying as terminally ill (p =.776). Conclusions: In this sample, patients’ desire for information about their cancer and prognosis was strongly associated with higher adherence to oral anticancer therapy over the following three months. Yet, this association may be stronger among those who do not identify as terminally ill. Targeted interventions that support patients who prefer fewer details about their illness and prognosis may improve medication adherence.
Novel use of an objective scoring rubric to guide inpatient chemotherapy stewardship.
Authors: Aarti Sonia Bhardwaj, Priya Jain, Damaris Peralta Hernandez, Shivani Handa, Giulia Petrone, Justine Anderson, Nobel Chowdhury, Kendra Yum, Deukwoo Kwon, John Mato, Natalie S Berger, Cardinale B. Smith
Journal: Journal of Clinical Oncology (2022)

20 Background: The cost of cancer care is an enormous healthcare burden. Most inpatient chemotherapy is not reimbursed because of diagnosis-related group codes. We have previously reported inpatient chemotherapy and immunotherapy (IC) is associated with poorer outcomes for patients with advanced stage solid tumor (ST) vs hematologic malignancy (HM) patients. 1 We piloted the use of a novel objective scoring rubric to guide and automate IC stewardship at an academic cancer center to decrease the inappropriate use of inpatient administration of costly therapies in patients especially at the end of life. Methods: Using an iterative process, an interdisciplinary group of physicians, nurses and pharmacists developed objective criteria of patient, cancer and treatment factors to guide chemotherapy stewardship. IC that is on formulary and being given as standard of care (i.e., induction of leukemia) are automatically approved. IC that is non-formulary requires evaluation using the developed criteria. Treatment factors include information on the level of existing evidence to support use: type and phase of trial, FDA and NCCN approvals. Patient factors include: performance status, line and goal of therapy. The scoring rubric positively weights regimens with strong levels of evidence or positive patient factors and negatively weights regimens with poor levels of evidence and adverse patient factors. Clinicians must complete the criteria via a form in RedCap. Upon completion, a score is automatically calculated by the tool and 2 disease specific physicians and a clinical pharmacist review for accuracy. If the threshold score is met, IC is approved for inpatient administration and if it is not met, IC is not approved for administration. Results: From January 2022 until May 2022 there have been 30 cases reviewed. 50% were ST requests and 50% were for HM requests. 20 cases (67%) were approved and 8 cases (26%) were not. Two cases were retracted by the requestor. This resulted in cost savings of $63,920. Table illustrates clinical outcomes and characteristics of the approved cases. Conclusions: This pilot illustrates that 67% of the time our cancer physicians chose the administration of inpatient chemotherapy that aligned with objective criteria which is reassuring and serves to validate the use of this tool. Alternatively, this objective rubric prevented inappropriate administration of chemotherapy 26% of the time. Our pilot indicates that there is a role for an objective tool for automated inpatient chemotherapy stewardship. Reference: Evaluation of inpatient chemotherapy among patients with cancer. Petrone G et al. JCO.2022.40.16_suppl.6566.[Table: see text]
How granularity of data matters in understanding and accelerating racial diversity in U.S. clinical trials.
Authors: Ted Bebi, Rachel Horovitz, Kevin Blum, Robbie Buderi, Pierre-Louis Bourlon, Elizabeth W. Lamont, Stephanie Chamberlain, Fareed Melhem
Journal: Journal of Clinical Oncology (2022)

88 Background: Historically, US clinical trials have been shown to recruit disproportionately large percentages of White patients, raising concerns about the generalizability of clinical trial results to underrepresented racial minority patient populations. Because of this, the FDA has recently reiterated its guidance stating that clinical trials need to reflect the demographic distribution of the US. In this research, we sought to understand how participation of Black patients varies by therapeutic area and geography within the US. Methods: Studying patient-level clinical trial data from an industry-leading historical clinical trial data repository of over 8 million patients from 27,000 clinical trials, we assessed the racial composition of US interventional trials across indications from 2010 to 2021 which encompassed 433,822 clinical trial participants across 2,997 trials. We also analyzed participants’ racial composition within the subset of trials from three distinct therapeutic areas (i.e., oncology n = 118,194, cardiovascular n = 12,281, central nervous system n = 35,533) and distinct sites over the same period. Results: The racial distribution of clinical trial participants in the US across all therapeutic areas was 78% White, 15% Black, and 3% Asian. Within the three distinct therapeutic areas, the proportion of Black clinical trial participants varied, with oncology trials reporting 8.5% Black participants, cardiovascular trials reporting 15.3% Black participants, and central nervous system trials reporting 19.9% Black participants. Black participation also varied within a therapeutic area, depending on the indication, as well as by site, with individual sites contributing differently to the racial diversity of trials. Conclusions: Our analysis shows that US interventional trials enroll 15% Black participants, appearing consistent with the 2020 US Census, which estimates that 14.6% of Americans are Black. However, more granular analyses at the level of therapeutic area, indication and site suggest substantial variation in Black participation in clinical trials including a gap in Black representation in oncology trials vs. US Census estimates. This research suggests that aggregate estimates of racial enrollment may mask dramatic variation by other factors like granularity of disease area and geographic location. The study of historic clinical trial data may yield useful insights for accelerating diverse representation in clinical trials.
Creating a single point of referral and standardized care pathway for patients with melanoma to improve access to care.
Authors: Sydney Rubin Fitzgerald, Bailey Hanson, Andrew Phillip Loehrer
Journal: Journal of Clinical Oncology (2022)

127 Background: Access to care is often a challenge for healthcare organizations  especially as pressures on time increase and workforce availability decreases  and is often complex to solve. In this quality improvement (QI) initiative, a team from a rural academic medical center deployed the Lean Six Sigma approach to develop a two-pronged method that reduced the median time to first visit for new melanoma patients. Methods: The project team deployed the Define, Measure, Analyze, Improve, and Control (DMAIC) processes to address access for melanoma patients after the healthcare organization set a goal that 55% of new specialty care patients be seen within 10 days. Define: Concern was raised by the melanoma clinical care team that the lack of a well-defined and standardized referral workflow for melanoma patients could delay patient care. Measure: Data from the electronic medical record (EMR) indicated that only 31% of incoming referrals were seen within 10 days, and the median number of days to first visit was 15, or 50% over the organizational standard. Analyze: Analysis found considerable waste in the existing referral system. First, untrained staff made referral and routing decisions, meaning patients could potentially be seen by inappropriate departments based on the assessment of those not specialized in melanoma care and treatment. This led to the second area of waste: rework. Every referral had to be reviewed by multiple staff in several departments to ensure the referral made was appropriate based on the characteristics of disease. This was a very labor-intensive processes that allowed too many patients to slip through the cracks of the system. Improve: Two interventions were deployed to address the identified waste. First, a centralized referral point for all melanomas monitored by the Program Coordinator. Second, a referral questionnaire developed by an interdisciplinary team to guide where routine cases should be referred. Early results show that the interventions had marked impact on the time to first appointment for all referrals, whether originating inside of the organization or out. After the intervention 54% of newly referred patients were seen within 10 days. Results: Control: A standard report was built to support the project team in monthly monitoring of the KPI, days from referral to patient seen. The report is monitored by a dedicated Program Coordinator who can escalate any issues during regular interdisciplinary care team meetings. Conclusions: Improvements in access can be achieved by adopting standard work that is targeted to reduce waste in the referral workflow. The model developed by this QI initiative is easily replicable and may be especially useful for interdisciplinary teams who provide care to complex diseases.[Table: see text]